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# Copyright 2022-2024 ETSI OSG/SDG TeraFlowSDN (TFS) (https://tfs.etsi.org/)
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import time, json
from typing import Dict
from common.tools.kafka.Variables import KafkaTopic
from analytics.backend.service.AnalyticsBackendService import AnalyticsBackendService
from analytics.backend.tests.messages import get_kpi_id_list, get_operation_list, get_threshold_dict
from .messages import create_analyzer, create_analyzer_dask
from threading import Thread, Event
from ..service.DaskStreaming import DaskStreamer
LOGGER = logging.getLogger(__name__)
###########################
# Tests Implementation of Telemetry Backend
###########################
# --- "test_validate_kafka_topics" should be run before the functionality tests ---
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# def test_validate_kafka_topics():
# LOGGER.debug(" >>> test_validate_kafka_topics: START <<< ")
# response = KafkaTopic.create_all_topics()
# assert isinstance(response, bool)
# --- To test Dask Streamer functionality ---
# def test_StartDaskStreamer(): # Directly from the Streamer class
# LOGGER.debug(" >>> test_StartSparkStreamer: START <<< ")
# stop_event = Event()
# kpi_list = ["1e22f180-ba28-4641-b190-2287bf446666", "6e22f180-ba28-4641-b190-2287bf448888", 'kpi_3']
# oper_list = ['avg', 'min', 'max',]
# thresholds = {
# 'avg_value': (10.0, 90.0),
# 'min_value': (5.0, 95.0),
# 'max_value': (15.0, 85.0),
# 'latency' : (2.0, 10.0)
# }
# # Start the DaskStreamer in a separate thread
# streamer_thread = Thread(
# target=DaskStreamer,
# args=("analytics_stream", kpi_list, oper_list, thresholds, stop_event),
# kwargs={
# "window_size": "60s",
# "win_slide_duration": "30s",
# "time_stamp_col": "time_stamp"
# }
# )
# streamer_thread.start()
# try:
# while True:
# time.sleep(10)
# except KeyboardInterrupt:
# LOGGER.info("KeyboardInterrupt received. Stopping streamer...")
# stop_event.set()
# streamer_thread.join()
# LOGGER.info("Streamer stopped gracefully.")
# --- To test Start Streamer functionality ---
# def test_StartDaskStreamer():
# LOGGER.debug(" >>> test_StartBaskStreamer: START <<< ")
# analyzer_obj = create_analyzer_dask()
# # LOGGER.info("Created Analyzer Object: {:}".format(analyzer_obj))
# analyzer_uuid = analyzer_obj.analyzer_id.analyzer_id.uuid
# analyzer_to_generate : Dict = {
# "algo_name" : analyzer_obj.algorithm_name,
# "input_kpis" : [k.kpi_id.uuid for k in analyzer_obj.input_kpi_ids],
# "output_kpis" : [k.kpi_id.uuid for k in analyzer_obj.output_kpi_ids],
# "oper_mode" : analyzer_obj.operation_mode,
# "thresholds" : json.loads(analyzer_obj.parameters["thresholds"]),
# "oper_list" : json.loads(analyzer_obj.parameters["oper_list"]),
# # "oper_list" : analyzer_obj.parameters["oper_list"],
# "window_size" : analyzer_obj.parameters["window_size"],
# "window_slider" : analyzer_obj.parameters["window_slider"],
# # "store_aggregate" : analyzer_obj.parameters["store_aggregate"]
# }
# AnalyticsBackendServiceObj = AnalyticsBackendService()
# LOGGER.info("Analyzer to be generated: {:}".format((analyzer_to_generate)))
# response = AnalyticsBackendServiceObj.StartDaskListener(analyzer_uuid, analyzer_to_generate)
# assert isinstance(response, bool)
# time.sleep(100)
# LOGGER.info('Initiating StopRequestListener...')
# # AnalyticsBackendServiceObj = AnalyticsBackendService()
# response = AnalyticsBackendServiceObj.StopDaskListener(analyzer_uuid)
# LOGGER.debug(str(response))
# assert isinstance(response, bool)
# --- To test Start Streamer functionality ---
# def test_StartSparkStreamer():
# LOGGER.debug(" >>> test_StartSparkStreamer: START <<< ")
# analyzer_obj = create_analyzer()
# analyzer_uuid = analyzer_obj.analyzer_id.analyzer_id.uuid
# analyzer_to_generate : Dict = {
# "algo_name" : analyzer_obj.algorithm_name,
# "input_kpis" : [k.kpi_id.uuid for k in analyzer_obj.input_kpi_ids],
# "output_kpis" : [k.kpi_id.uuid for k in analyzer_obj.output_kpi_ids],
# "oper_mode" : analyzer_obj.operation_mode,
# "thresholds" : json.loads(analyzer_obj.parameters["thresholds"]),
# "window_size" : analyzer_obj.parameters["window_size"],
# "window_slider" : analyzer_obj.parameters["window_slider"],
# # "store_aggregate" : analyzer_obj.parameters["store_aggregate"]
# }
# AnalyticsBackendServiceObj = AnalyticsBackendService()
# response = AnalyticsBackendServiceObj.StartSparkStreamer(analyzer_uuid, analyzer_to_generate)
# assert isinstance(response, bool)
# --- To TEST StartRequestListenerFunctionality
def test_StartRequestListener():
LOGGER.info('test_RunRequestListener')
AnalyticsBackendServiceObj = AnalyticsBackendService()
AnalyticsBackendServiceObj.stop_event = Event()
listener_thread = Thread(target=AnalyticsBackendServiceObj.RequestListener, args=())
listener_thread.start()
time.sleep(100)
# AnalyticsBackendServiceObj.stop_event.set()
# LOGGER.info('Backend termination initiated. waiting for termination... 10 seconds')
# listener_thread.join(timeout=10)
# assert not listener_thread.is_alive(), "RequestListener thread did not terminate as expected."
LOGGER.info('Completed test_RunRequestListener')
# def test_StopRequestListener():
# LOGGER.info('test_RunRequestListener')
# LOGGER.info('Initiating StartRequestListener...')
# AnalyticsBackendServiceObj = AnalyticsBackendService()
# response_thread = AnalyticsBackendServiceObj.StartRequestListener() # response is Tuple (thread, stop_event)
# # LOGGER.debug(str(response_thread))
# time.sleep(10)
# LOGGER.info('Initiating StopRequestListener...')
# AnalyticsBackendServiceObj = AnalyticsBackendService()
# response = AnalyticsBackendServiceObj.StopRequestListener(response_thread)
# LOGGER.debug(str(response))
# assert isinstance(response, bool)
# To independently tests the SparkListener functionality
# def test_SparkListener():
# LOGGER.info('test_RunRequestListener')
# AnalyticsBackendServiceObj = AnalyticsBackendService()
# response = AnalyticsBackendServiceObj.RunSparkStreamer(
# get_kpi_id_list(), get_operation_list(), get_threshold_dict()
# )
# LOGGER.debug(str(response))
# assert isinstance(response, bool)